Drug Targets and Biomarker Identification from Computational Study of Human Notch Signaling Pathway

Abstract

Notch signaling pathway is widely implicated in controlling various cellular functions, cell fate determination, and stem cell renewal in human but aberrant activity in cancer stem cells may cause different types of cancers. Understanding the complexity of this pathway to identify important targets for cancer therapy and to suppress the pathway activity without affecting the normal functions is of utmost importance to clinical and experimental pharmacologists. For developing therapeutic strategy, non availability of detailed molecular interactions, complex regulations and cross talks with other pathways pose a serious challenge to get a coherent understanding of this pathway. This motivated us to reconstruct the largest human cell specific Notch pathway with more number of molecules and interactions available from literatures and databases. To identify probable drug targets and biomarkers for cancer prognosis, we also performed computational study of the pathway using structural and logical analysis and identified important hub proteins, cross talks and feedback mechanisms. The model simulation is validated using reported mRNA expression profile in Glioblastoma cell line and the predictions not only show significant accuracy but also able to identify the undetermined expressions. From our simulation, to identify novel combinations of drug targetable proteins and better substitute for GAMMA SECRETASE inhibition, we proposed two alternative scenarios: partial suppression of Notch target proteins by NICD1 & HIF1A; and complete suppression by NICD1 & MAML, in Glioblastoma cell line. This reconstructed Notch signaling pathway and the computational analysis for identifying new biomarkers and combinatory drug targets will be useful for future in-vitro and in-vivo analysis to control different cancers. Keywords: